class_docstr: A stream that generates a rolling window of values from a stream.
  
  Parameters
  ----------
  window : int
      The size of the rolling window.
  min_periods : int, default 1
      The number of periods to wait before producing values from the aggregation
      function.
docstr: Computes a rolling mean from the underlying stream.
  
  Returns
  -------
  `Stream[float]`
      A rolling mean stream.
docstr_tok: ["Computes","a","rolling","mean","from","the","underlying","stream",".","Returns","--","--","--","-","`","Stream","[","float","]","`","A","rolling","mean","stream","."]
code: def mean(self) -> "Stream[float]":
      """Computes a rolling mean from the underlying stream.
  
      Returns
      -------
      `Stream[float]`
          A rolling mean stream.
      """
      func = np.nanmean if self.min_periods < self.window else np.mean
      return self.agg(func).astype("float")
  
imports: from typing import List, Callable
  import numpy
  from tensortrade.feed.core.base import Stream
  from tensortrade.feed.api.float import Float
label_desc: Use image node_id 7 for calling the Rolling obj's underlying member method code with example usage: obj.mean() and returns: self